Liver disorders, such as hepatitis, are major public health concerns. For example, hepatitis C is estimated to affect 200 million people worldwide. Patients with liver damage resulting from hepatitis C may develop chronic liver diseases, such as cirrhosis and hepatocellular carcinoma. Hepatitis C can be treated with interferon α and ribavirin. However, interferon α or ribavirin therapy causes significant side effects and is expensive. More importantly, only about 50% hepatitis C patients are responsive to the treatment. New therapies have been vigorously sought. Although several drug candidates are now being evaluated, the progress is rather slow due to a lack of appropriate systems for determining a patient's response to new therapies. Thus, there is a need for a reliable system and method for predicting a patient's response to treatment of hepatitis C and other liver disorders.
A patient's response to viral therapy is associated with various viral factors, e.g., the viral level, viral genotype, and mutation in certain viral proteins, and host factors, e.g., the patient's age, gender, race, host immune response, HLA alleles, and other genetic compositions, such as polymorphisms.
Single nucleotide polymorphisms (SNPs), a set of single nucleotide variants at genomic loci, are distributed throughout a genome. An SNP can be “allelic.” More specifically, due to polymorphism, some members of a species have the unmutated sequence (i.e., the wild-type allele) and others have a mutated sequence (i.e., the mutant allele). In humans, a polymorphism or a set of polymorphisms may be associated with a genetic disorder. In addition, patients having different SNP genotypes respond to the same treatment differently. Therefore, an SNP genotype of a patient is expected to provide individualized guidance for preventing and treating various human disorders.